Disaster risk layering choices
Retention and transfer options are compared on cost, speed of payout and 基差风险 across loss scenarios, to show how a mix of reserves, contingent credit and insurance performs.
GRA · Sovereign Capital Nexus
空间金融资本与危害、风险暴露和转型的交汇之处
Sovereign wealth and debt decisions are made under 深度不确定性 about commodity prices, climate pathways, disasters, geopolitics and demographic change. Decision analysis makes the trade-offs between saving, spending, insuring and borrowing explicit, and tests choices across many futures rather than a single forecast.
Decision analysis under uncertainty provides structured methods for choosing among options when outcomes are uncertain and objectives conflict. It makes trade-offs and value judgements explicit. In sovereign and public finance and capital markets and investment, decision analysis helps choose actions that perform acceptably across interconnected risks and uncertain futures. It clarifies when to act now and when to keep options open. The canonical description is on STEM Commons.
Retention and transfer options are compared on cost, speed of payout and 基差风险 across loss scenarios, to show how a mix of reserves, contingent credit and insurance performs.
Candidate deposit and withdrawal rules are run across many price and return paths and judged on how often they breach spending, saving or liquidity thresholds.
Multi-criteria analysis sets out how candidate allocations score against return, liquidity, domestic policy goals and governance risk, with the weights made explicit.
团队遵循该方法时会使用的界面:其指标、状态与决策。名称为示例,数值仅作示意。
Sovereign capital · Decision analysis for sovereign · Run R-9903
| Assets under management | 对数正态 | local bn, stated | 专家判断征询 |
| Liquidity tranche cover | 正常 | months of imports, stated | 专家判断征询 |
| Drawdown in severe scenario | 正常 | of fund, stated | 专家判断征询 |
| Domestic investment share | 正常 | of fund, stated | 专家判断征询 |
| 数据 | 角色 | 标签 |
|---|---|---|
| Scenario sets for prices, climate and demography | Futures against which choices are tested | 模型估算 |
| Catastrophe risk model outputs | Loss distributions by layer | 模型估算 |
| 专家意见征询 records | Probabilities where data are thin | 估算 |
| Instrument terms and pricing | Cost of each financing option | 已发布统计 |
债务路径的分布,以及期末超过关注阈值的份额,是主权投资者和评级分析师从扇形图中读取的内容。这是带有明示示意数值的教学模型,不是预测。
控制措施
读数
| 年份 | 10% | 25% | 中位数 | 75% | 90% |
|---|---|---|---|---|---|
| 0 | 70.0 | 70.0 | 70.0 | 70.0 | 70.0 |
| 1 | 69.0 | 69.7 | 70.7 | 71.9 | 73.1 |
| 2 | 69.0 | 70.3 | 71.5 | 73.1 | 74.5 |
| 3 | 68.9 | 70.5 | 72.7 | 74.6 | 76.5 |
| 4 | 69.1 | 71.0 | 73.4 | 75.6 | 77.7 |
| 5 | 69.4 | 71.7 | 74.2 | 76.8 | 79.2 |
| 6 | 69.9 | 72.2 | 74.9 | 77.8 | 81.0 |
| 7 | 70.0 | 72.7 | 75.5 | 78.8 | 82.2 |
| 8 | 70.3 | 73.1 | 76.2 | 80.3 | 83.2 |
| 9 | 70.8 | 73.8 | 77.3 | 81.2 | 84.9 |
| 10 | 71.4 | 74.3 | 78.2 | 82.1 | 86.5 |
No observed data enters this model: it runs on the teaching values set by the controls, to be replaced with a programme’s own evidence.
贯穿六大支柱,由 Nexus Consortium 牵头
| 核查 | 如何开展 |
|---|---|
| 敏感性分析 | Results are recomputed with altered probabilities, weights and costs to show which choices are fragile |
| Performance across scenarios | Choices are judged on how they perform across the whole scenario set, not on a single central case |
| 回顾性审查 | Past decisions are compared with outcomes to improve elicitation and scenario design |
结果取决于征询得到的概率与偏好,而这些可能存在偏倚。深度不确定性可能使期望值比较产生误导。
风险官、监管者或财政部会要求的风险暴露、损失、情景和资本视图,以及它们据以报告的框架。结构遵循监管和精算实务。数值为说明性:绝非价格、评级或建议。
The indicators a risk officer, supervisor or ministry of finance reads first on decision analysis for sovereign choices.
| 指标 | 单位 | 谁来阅读 | 框架 |
|---|---|---|---|
| 公共债务 | 占 GDP 的 % | 财政部、IMF | 债务可持续性框架 |
| 总融资需求 | 每年占 GDP 的 % | 财政部、投资者 | 债务可持续性框架 |
| 或有负债 | 占 GDP 的 %,按来源划分 | 财政部门 | 财政风险声明 |
| 利息占收入的比重 | 占收入的百分比 | 财政部、评级使用方 | 公共财政统计 |
| 主权利差 | 高于基准的基点 | 投资者、债务管理者 | 市场数据 |
| CET1 比率 | 占风险加权资产的百分比 | 银行、监管机构 | 巴塞尔框架 |
| 流动性覆盖率 | 压力流出的 % | 银行、中央银行 | 巴塞尔框架 |
报告 is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
切勿发送个人数据、敏感基础设施细节或您无权分享的任何内容。贡献在使用前会经过审查;发送贡献不赋予署名权或编辑权,赞助也绝不能换取研究结论。
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